Deconvolution Beamforming Algorithm Based Abnormal Noise Fault Identification of Dry-Type Transformer
To improve the accuracy of the conventional beamforming location algorithm, the deconvolution beamforming algorithm is proposed for the abnormal noise fault identification of dry-type transformer. The basic principle of deconvolution beamforming algorithm is analyzed, and its applicability to the dr...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
State Grid Energy Research Institute
2022-02-01
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| Series: | Zhongguo dianli |
| Subjects: | |
| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202004162 |
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| Summary: | To improve the accuracy of the conventional beamforming location algorithm, the deconvolution beamforming algorithm is proposed for the abnormal noise fault identification of dry-type transformer. The basic principle of deconvolution beamforming algorithm is analyzed, and its applicability to the dry-type transformer abnormal-noise fault identification is verified. A dry-type transformer fault identification method based on the accurate location of abnormal-noise is studied, where the feature recognition of voice print is considered. The concept of "the energy ratio of high-frequency characteristic peak" is firstly proposed to quantify the severity of mechanical abnormal noise. Finally, experimental test and field verification validate the effectiveness and accuracy of the proposed method. |
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| ISSN: | 1004-9649 |